



'''simple docstring'''



import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List

import git
import torch
from torch.utils.data import Dataset

from transformers import BartTokenizer, RagTokenizer, TaTokenizer
def        UpperCAmelCase (    A	:					List[str]       ,		A	:					List[str]       ,		A	:					int       ,		A	:					List[str]       ,		A	:					Optional[Any]=True       ,		A	:					Optional[Any]="pt"					):
							SCREAMING_SNAKE_CASE       :   str         =      {'''add_prefix_space''': True} if isinstance(A       ,		A					) and not line.startswith(''' '''					) else {}
							SCREAMING_SNAKE_CASE       :   Dict         =      padding_side
							return tokenizer(
							    [line]       ,		max_length=A       ,		padding='''max_length''' if pad_to_max_length else None       ,		truncation=A       ,		return_tensors=A       ,		add_special_tokens=A       ,		**A       ,		)
def        UpperCAmelCase (    A	:					Union[str, Any]       ,		A	:					Any       ,		A	:					Optional[int]=None       ,		):
							SCREAMING_SNAKE_CASE       :   Union[str, Any]         =      input_ids.ne(A					).any(dim=0					)
							if attention_mask is None:
														return input_ids[:, keep_column_mask]
							else:
														return (input_ids[:, keep_column_mask], attention_mask[:, keep_column_mask])
class 						lowerCamelCase_				(       snake_case_      ):







						def __init__(	self :   Tuple					,     lowerCAmelCase__ :   Tuple					,     lowerCAmelCase__ :   Dict					,     lowerCAmelCase__ :   Any					,     lowerCAmelCase__ :   Optional[int]					,     lowerCAmelCase__ :   Optional[int]="train"					,     lowerCAmelCase__ :   int=None					,     lowerCAmelCase__ :   int=None					,     lowerCAmelCase__ :   Dict=None					,     lowerCAmelCase__ :   Tuple=""					,     ):

													"""simple docstring"""
													super().__init__()
													SCREAMING_SNAKE_CASE       :   List[Any]         =      Path(lowerCAmelCase__					).joinpath(type_path + '''.source'''					)
													SCREAMING_SNAKE_CASE       :   Optional[int]         =      Path(lowerCAmelCase__					).joinpath(type_path + '''.target'''					)
													SCREAMING_SNAKE_CASE       :   str         =      self.get_char_lens(self.src_file					)
													SCREAMING_SNAKE_CASE       :   Optional[int]         =      max_source_length
													SCREAMING_SNAKE_CASE       :   List[Any]         =      max_target_length
													assert min(self.src_lens					) > 0, F"""found empty line in {self.src_file}"""
													SCREAMING_SNAKE_CASE       :   List[Any]         =      tokenizer
													SCREAMING_SNAKE_CASE       :   List[str]         =      prefix
													if n_obs is not None:
																				SCREAMING_SNAKE_CASE       :   str         =      self.src_lens[:n_obs]
													SCREAMING_SNAKE_CASE       :   Tuple         =      src_lang
													SCREAMING_SNAKE_CASE       :   Union[str, Any]         =      tgt_lang







						def __len__(	self :   int					):

													"""simple docstring"""
													return len(self.src_lens					)







						def __getitem__(	self :   List[str]					,     lowerCAmelCase__ :   Dict					):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE       :   Optional[Any]         =      index + 1  # linecache starts at 1
													SCREAMING_SNAKE_CASE       :   List[str]         =      self.prefix + linecache.getline(str(self.src_file					)					,     lowerCAmelCase__					).rstrip('''\n'''					)
													SCREAMING_SNAKE_CASE       :   List[Any]         =      linecache.getline(str(self.tgt_file					)					,     lowerCAmelCase__					).rstrip('''\n'''					)
													assert source_line, F"""empty source line for index {index}"""
													assert tgt_line, F"""empty tgt line for index {index}"""

													# Need to add eos token manually for T5
													if isinstance(self.tokenizer					,     lowerCAmelCase__					):
																				source_line += self.tokenizer.eos_token
																				tgt_line += self.tokenizer.eos_token

													# Pad source and target to the right
													SCREAMING_SNAKE_CASE       :   Dict         =      (
													    self.tokenizer.question_encoder if isinstance(self.tokenizer					,     lowerCAmelCase__					) else self.tokenizer
													)
													SCREAMING_SNAKE_CASE       :   Tuple         =      self.tokenizer.generator if isinstance(self.tokenizer					,     lowerCAmelCase__					) else self.tokenizer

													SCREAMING_SNAKE_CASE       :   List[str]         =      encode_line(lowerCAmelCase__					,     lowerCAmelCase__					,     self.max_source_length					,     '''right'''					)
													SCREAMING_SNAKE_CASE       :   Dict         =      encode_line(lowerCAmelCase__					,     lowerCAmelCase__					,     self.max_target_length					,     '''right'''					)

													SCREAMING_SNAKE_CASE       :   int         =      source_inputs['''input_ids'''].squeeze()
													SCREAMING_SNAKE_CASE       :   Union[str, Any]         =      target_inputs['''input_ids'''].squeeze()
													SCREAMING_SNAKE_CASE       :   int         =      source_inputs['''attention_mask'''].squeeze()
													return {
													    "input_ids": source_ids,
													    "attention_mask": src_mask,
													    "decoder_input_ids": target_ids,
													}







						@staticmethod
						def        __lowercase     (	lowerCAmelCase__ :   List[Any]					):

													"""simple docstring"""
													return [len(lowerCAmelCase__					) for x in Path(lowerCAmelCase__					).open().readlines()]







						def        __lowercase     (	self :   List[Any]					,     lowerCAmelCase__ :   List[Any]					):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE       :   List[Any]         =      torch.stack([x['''input_ids'''] for x in batch]					)
													SCREAMING_SNAKE_CASE       :   Optional[int]         =      torch.stack([x['''attention_mask'''] for x in batch]					)
													SCREAMING_SNAKE_CASE       :   List[Any]         =      torch.stack([x['''decoder_input_ids'''] for x in batch]					)
													SCREAMING_SNAKE_CASE       :   List[Any]         =      (
													    self.tokenizer.generator.pad_token_id
													    if isinstance(self.tokenizer					,     lowerCAmelCase__					)
													    else self.tokenizer.pad_token_id
													)
													SCREAMING_SNAKE_CASE       :   Optional[Any]         =      (
													    self.tokenizer.question_encoder.pad_token_id
													    if isinstance(self.tokenizer					,     lowerCAmelCase__					)
													    else self.tokenizer.pad_token_id
													)
													SCREAMING_SNAKE_CASE       :   Union[str, Any]         =      trim_batch(lowerCAmelCase__					,     lowerCAmelCase__					)
													SCREAMING_SNAKE_CASE       ,SCREAMING_SNAKE_CASE       :   int         =      trim_batch(lowerCAmelCase__					,     lowerCAmelCase__					,     attention_mask=lowerCAmelCase__					)
													SCREAMING_SNAKE_CASE       :   int         =      {
													    '''input_ids''': source_ids,
													    '''attention_mask''': source_mask,
													    '''decoder_input_ids''': y,
													}
													return batch


lowerCAmelCase_  :							List[str]             =    getLogger(__name__)
def        UpperCAmelCase (    A	:					List[List]					):
							return list(itertools.chain.from_iterable(A					)					)
def        UpperCAmelCase (    A	:					str					):
							SCREAMING_SNAKE_CASE       :   Optional[Any]         =      get_git_info()
							save_json(A       ,		os.path.join(A       ,		'''git_log.json'''					)					)
def        UpperCAmelCase (    A	:					Any       ,		A	:					Union[str, Any]       ,		A	:					List[str]=4       ,		**A	:					Tuple					):
							with open(A       ,		'''w'''					) as f:
														json.dump(A       ,		A       ,		indent=A       ,		**A					)
def        UpperCAmelCase (    A	:					Dict					):
							with open(A					) as f:
														return json.load(A					)
def        UpperCAmelCase (    ):
							SCREAMING_SNAKE_CASE       :   Optional[int]         =      git.Repo(search_parent_directories=A					)
							SCREAMING_SNAKE_CASE       :   Dict         =      {
							    '''repo_id''': str(A					),
							    '''repo_sha''': str(repo.head.object.hexsha					),
							    '''repo_branch''': str(repo.active_branch					),
							    '''hostname''': str(socket.gethostname()					),
							}
							return repo_infos
def        UpperCAmelCase (    A	:					Callable       ,		A	:					Iterable					):
							return list(map(A       ,		A					)					)
def        UpperCAmelCase (    A	:					List[Any]       ,		A	:					Union[str, Any]					):
							with open(A       ,		'''wb'''					) as f:
														return pickle.dump(A       ,		A					)
def        UpperCAmelCase (    A	:					List[Any]					):

							def remove_articles(A	:					Dict					):
														return re.sub(r'''\b(a|an|the)\b'''       ,		''' '''       ,		A					)

							def white_space_fix(A	:					Union[str, Any]					):
														return " ".join(text.split()					)

							def remove_punc(A	:					Optional[int]					):
														SCREAMING_SNAKE_CASE       :   List[Any]         =      set(string.punctuation					)
														return "".join(ch for ch in text if ch not in exclude					)

							def lower(A	:					List[Any]					):
														return text.lower()

							return white_space_fix(remove_articles(remove_punc(lower(A					)					)					)					)
def        UpperCAmelCase (    A	:					Any       ,		A	:					int					):
							SCREAMING_SNAKE_CASE       :   Dict         =      normalize_answer(A					).split()
							SCREAMING_SNAKE_CASE       :   Optional[Any]         =      normalize_answer(A					).split()
							SCREAMING_SNAKE_CASE       :   List[str]         =      Counter(A					) & Counter(A					)
							SCREAMING_SNAKE_CASE       :   Dict         =      sum(common.values()					)
							if num_same == 0:
														return 0
							SCREAMING_SNAKE_CASE       :   Union[str, Any]         =      1.0 * num_same / len(A					)
							SCREAMING_SNAKE_CASE       :   int         =      1.0 * num_same / len(A					)
							SCREAMING_SNAKE_CASE       :   int         =      (2 * precision * recall) / (precision + recall)
							return fa
def        UpperCAmelCase (    A	:					Optional[int]       ,		A	:					Union[str, Any]					):
							return normalize_answer(A					) == normalize_answer(A					)
def        UpperCAmelCase (    A	:					List[str]       ,		A	:					List[str]					):
							assert len(A					) == len(A					)
							SCREAMING_SNAKE_CASE       :   str         =      0
							for hypo, pred in zip(A       ,		A					):
														em += exact_match_score(A       ,		A					)
							if len(A					) > 0:
														em /= len(A					)
							return {"em": em}
def        UpperCAmelCase (    A	:					Optional[int]					):
							return model_prefix.startswith('''rag'''					)






def        UpperCAmelCase (    A	:					List[Any]       ,		A	:					int       ,		A	:					Any					):
							SCREAMING_SNAKE_CASE       :   int         =      {p: p for p in extra_params}
							# T5 models don't have `dropout` param, they have `dropout_rate` instead
							SCREAMING_SNAKE_CASE       :   List[Any]         =      '''dropout_rate'''
							for p in extra_params:
														if getattr(A       ,		A       ,		A					):
																					if not hasattr(A       ,		A					) and not hasattr(A       ,		equivalent_param[p]					):
																												logger.info('''config doesn\'t have a `{}` attribute'''.format(A					)					)
																												delattr(A       ,		A					)
																												continue
																					SCREAMING_SNAKE_CASE       :   str         =      p if hasattr(A       ,		A					) else equivalent_param[p]
																					setattr(A       ,		A       ,		getattr(A       ,		A					)					)
																					delattr(A       ,		A					)
							return hparams, config









'''simple docstring'''



def        UpperCAmelCase (    A	:					int					):
							if not isinstance(A       ,		A					):
														SCREAMING_SNAKE_CASE       :   List[str]         =      F"""Input value of [number={number}] must be an integer"""
														raise TypeError(A					)
							if number < 0:
														return False
							SCREAMING_SNAKE_CASE       :   List[str]         =      number * number
							while number > 0:
														if number % 10 != number_square % 10:
																					return False
														number //= 10
														number_square //= 10
							return True


if __name__ == "__main__":
							import doctest

							doctest.testmod()




